Senior Machine Learning Engineer

Bjak·Germanysenior

In short

→Ingeniero ML sénior que construye y entrega sistemas de IA proactiva en producción con alta confiabilidad.
→Trabajas en todo el ciclo: datos, entrenamiento, inferencia, monitoreo y mejora continua con señales del mundo real.
→Destacan sistemas de IA que operan durante largos períodos con contexto persistente y mínimo error (hallucinaciones).

No se menciona requerimiento de inglés.

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What they ask for

✓Experiencia probada en construir y desplegar sistemas de ML con usuarios reales.
✓Capacidad para manejar problemas ambiguos y entregar soluciones prácticas end-to-end.
✓Dominio de código productivo de alta calidad y pensamiento sistémico, no solo scripts.
✓Experiencia real con problemas de producción: latencia, coste, fiabilidad y seguridad.
✓Habilidades para depurar fallos de modelos usando señales reales del entorno de producción.
✓Capacidad de mentorear a otros ingenieros ML y elevar el estándar técnico del equipo.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonPyTorchJAXGPU-based trainingGPU-based inferenceProduction ML systemsData pipelinesInference pipelinesMonitoring systemsReal-world feedback loops

Who should you write to at Bjak?

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About ActAI There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations. Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things. Role As a Senior Member of Technical Staff, Machine Learning, you are an independent owner of critical ML subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale. This is a hands-on, high-impact role focused on depth. Focus Build core ML systems that power a proactive, long-horizon AI product. Own work end-to-end: data preparation, training, evaluation, inference, and iteration. Turn research ideas into working systems that run reliably in production. Debug model failures and system issues using real production signals. Iterate quickly: ship, measure outcomes, refine, and repeat. Collaborate closely with research, product, and engineering to deliver real user impact. Mentor and review work from other ML engineers through example and technical judgment. Tech Stack Python PyTorch / JAX GPU-based training and inference systems Ideal Experience You have built and shipped ML systems used by real users. You understand how modern ML models behave — and misbehave — in production. You write strong, production-quality code and think in systems, not scripts. You take ownership, work independently, and push work across the finish line. You learn fast, communicate clearly, and improve through iteration. Outcomes ML models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets. Complex production issues are monitored, debugged, and resolved with minimal disruption. Training, inference, and data pipelines are robust, scalable, and maintainable over time. Drives measurable improvements in ML systems based on real-world signals and user feedback. Provides mentorship and technical guidance to peers, raising the overall ML engineering standard. Collaborates cross-functionally to ensure ML features integrate seamlessly into products and meet business goals. How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview process If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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